面向单词的补全暗示器（ElasticSearch 5.x）

Question

ElasticSearch5.x对Suggester API（文档）进行了一些（突破性的）更改。最显著的变化如下：

完成建议器是面向文档的

{
   "my-index": {
      "mappings": {
         "users": {
            "properties": {
               "firstName": {
                  "type": "text"
               },
               "lastName": {
                  "type": "text"
               },
               "suggest": {
                  "type": "completion",
                  "analyzer": "simple"
               }
            }
         }
      }
   }
}

{
   "_index": "my-index",
   "_type": "users",
   "_id": "1",
   "_source": {
      "firstName": "John",
      "lastName": "Doe",
      "suggest": [
         {
            "input": [
               "John",
               "Doe"
            ]
         }
      ]
   }
},
{
   "_index": "my-index",
   "_type": "users",
   "_id": "2",
   "_source": {
      "firstName": "John",
      "lastName": "Smith",
      "suggest": [
         {
            "input": [
               "John",
               "Smith"
            ]
         }
      ]
   }
}

和按本查询：

POST /my-index/_suggest?pretty
{
    "my-suggest" : {
        "text" : "joh",
        "completion" : {
            "field" : "suggest"
        }
    }
}

它产生以下结果：

{
   "_shards": {
      "total": 5,
      "successful": 5,
      "failed": 0
   },
   "my-suggest": [
      {
         "text": "joh",
         "offset": 0,
         "length": 3,
         "options": [
            {
               "text": "John",
               "_index": "my-index",
               "_type": "users",
               "_id": "1",
               "_score": 1,
               "_source": {
                 "firstName": "John",
                 "lastName": "Doe",
                 "suggest": [
                    {
                       "input": [
                          "John",
                          "Doe"
                       ]
                    }
                 ]
               }
            },
            {
               "text": "John",
               "_index": "my-index",
               "_type": "users",
               "_id": "2",
               "_score": 1,
               "_source": {
                 "firstName": "John",
                 "lastName": "Smith",
                 "suggest": [
                    {
                       "input": [
                          "John",
                          "Smith"
                       ]
                    }
                 ]
               }
            }
         ]
      }
   ]
}

简而言之，对于文本“joh”的补全建议，返回了两（2）个文档-John的文档和text属性的值都相同。

{
   "_shards": {
      "total": 5,
      "successful": 5,
      "failed": 0
   },
   "my-suggest": [
      {
         "text": "joh",
         "offset": 0,
         "length": 3,
         "options": [
          "John"
         ]
      }
   ]
}

null

为了克服第二点，仅仅索引单个单词是不够的，因为您还需要将所有单词映射到文档，以便适当地缩小自动完成的后续单词。这样，您实际上会遇到与查询原始索引相同的问题。因此，附加索引不再有意义。

Answer 1

正如注释中所暗示的，另一种不获取重复文档的方法是为firstname字段创建一个子字段，其中包含该字段的ngrams。首先，定义映射，如下所示：

PUT my-index
{
  "settings": {
    "analysis": {
      "analyzer": {
        "completion_analyzer": {
          "type": "custom",
          "filter": [
            "lowercase",
            "completion_filter"
          ],
          "tokenizer": "keyword"
        }
      },
      "filter": {
        "completion_filter": {
          "type": "edge_ngram",
          "min_gram": 1,
          "max_gram": 24
        }
      }
    }
  },
  "mappings": {
    "users": {
      "properties": {
        "autocomplete": {
          "type": "text",
          "fields": {
            "raw": {
              "type": "keyword"
            },
            "completion": {
              "type": "text",
              "analyzer": "completion_analyzer",
              "search_analyzer": "standard"
            }
          }
        },
        "firstName": {
          "type": "text"
        },
        "lastName": {
          "type": "text"
        }
      }
    }
  }
}

然后索引几个文档：

POST my-index/users/_bulk
{"index":{}}
{ "firstName": "John", "lastName": "Doe", "autocomplete": "John Doe"}
{"index":{}}
{ "firstName": "John", "lastName": "Deere", "autocomplete": "John Deere" }
{"index":{}}
{ "firstName": "Johnny", "lastName": "Cash", "autocomplete": "Johnny Cash" }

然后，您可以查询Joh，并为John获得一个结果，为Johnny获得另一个结果

{
  "size": 0,
  "query": {
    "term": {
      "autocomplete.completion": "john d"
    }
  },
  "aggs": {
    "suggestions": {
      "terms": {
        "field": "autocomplete.raw"
      }
    }
  }
}

{
  "aggregations": {
    "suggestions": {
      "doc_count_error_upper_bound": 0,
      "sum_other_doc_count": 0,
      "buckets": [
        {
          "key": "John Doe",
          "doc_count": 1
        },
        {
          "key": "John Deere",
          "doc_count": 1
        }
      ]
    }
  }
}

ES 7.2引入了一个名为search_as_you_type的新数据类型，它在本地允许这种行为。请参阅：https://www.elastic.co/guide/en/elasticsearch/reference/7.2/search-as-you-type.html